Validity of the MacDonald triad as a forensic construct: Links with psychopathology and patterns of aggression in sex offenders
Bibliographic record
Abstract
Purpose The MacDonald triad is composed of three developmental markers, including cruelty to animals, firesetting, and enuresis after the age of 5. Although there has been considerable interest in this construct initially, research has produced inconsistent results regarding its validity in terms of distinguishing between offender and non‐offender populations, or predicting future offences. The current study investigated the links between the triad, dimensions of psychopathology, and trajectories of aggression in a sample of 254 rapists previously collected from a single forensic mental health institution in the United States. Method A retrospective temporal design was used to examine associations between variables in a sequence of ten offences. Results Latent structure analyses yielded a two‐class solution for the triad indicators, a five‐dimensional model for psychopathology and three trajectories for the aggression variables over a sequence of ten offences. Univariate analyses revealed that the class characterized primarily by a high prevalence of cruelty to animals and firesetting was associated with a higher level of antisocial and aggressive traits, as well as with a trajectory of offending featuring higher levels of expressive aggression, at least during the first few offences in the sequence. These associations were large and weak‐to‐moderate in magnitude, respectively. Conclusions If replicated, these findings may suggest that a particular subgroup of sex offenders showing components of the triad are at particular risk of developing antisocial features, thus impacting the level of risk they pose to potential victims and the community.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".